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    <title>cdft</title>
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    <center>Scilab Function</center>
    <div align="right">Last update : Dec 1997</div>
    <p>
      <b>cdft</b> -  cumulative distribution function Student's T distribution</p>
    <h3>
      <font color="blue">Calling Sequence</font>
    </h3>
    <dl>
      <dd>
        <tt>[P,Q]=cdft("PQ",T,Df)  </tt>
      </dd>
      <dd>
        <tt>[T]=cdft("T",Df,P,Q)  </tt>
      </dd>
      <dd>
        <tt>[Df]=cdft("Df",P,Q,T)  </tt>
      </dd>
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      <font color="blue">Parameters</font>
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    <ul>
      <li>
        <tt>
          <b>P,Q,T,Df</b>
        </tt>: six real vectors of the same size.</li>
      <li>
        <tt>
          <b>P,Q (Q=1-P)  </b>
        </tt>: The integral from -infinity to t of the t-density. Input range: (0,1].</li>
      <li>
        <tt>
          <b>T</b>
        </tt>: Upper limit of integration of the t-density. Input range: ( -infinity, +infinity). Search range: [ -1E150, 1E150 ]</li>
      <li>
        <tt>
          <b>DF:  </b>
        </tt>Degrees of freedom of the t-distribution. Input range: (0 , +infinity). Search range: [1e-300, 1E10]</li>
    </ul>
    <h3>
      <font color="blue">Description</font>
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    <p>
    Calculates any one parameter of the T distribution given
    values for the others.</p>
    <p>
    Formula  26.5.27  of   Abramowitz   and  Stegun,   Handbook   of
    Mathematical Functions  (1966) is used to reduce the computation
    of the cumulative distribution function to that of an incomplete
    beta.</p>
    <p>
    Computation of other parameters involve a seach for a value that
    produces  the desired  value  of P.   The search relies  on  the
    monotinicity of P with the other parameter.</p>
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